Budiharto Widodo
School of Computer Science, Bina Nusantara University, Jakarta, Indonesia.
Comput Intell Neurosci. 2015;2015:745823. doi: 10.1155/2015/745823. Epub 2015 May 24.
For specific purpose, vision-based surveillance robot that can be run autonomously and able to acquire images from its dynamic environment is very important, for example, in rescuing disaster victims in Indonesia. In this paper, we propose architecture for intelligent surveillance robot that is able to avoid obstacles using 3 ultrasonic distance sensors based on backpropagation neural network and a camera for face recognition. 2.4 GHz transmitter for transmitting video is used by the operator/user to direct the robot to the desired area. Results show the effectiveness of our method and we evaluate the performance of the system.
对于特定用途而言,能够自主运行并从动态环境中获取图像的基于视觉的监控机器人非常重要,例如在印度尼西亚救援灾难受害者的场景中。在本文中,我们提出了一种智能监控机器人的架构,该机器人能够使用基于反向传播神经网络的3个超声波距离传感器和一个用于人脸识别的摄像头来避障。操作员/用户使用用于传输视频的2.4 GHz发射器将机器人引导至所需区域。结果表明了我们方法的有效性,并且我们评估了系统的性能。